Identités et loyautés des auteurs et peintres russes de l'Estonie post-soviétique
Bibliographic record
Abstract
After five decades of Soviet occupation, Estonia’s population included a large Russian minority. In order to distance itself from Russia, and to “correct” the harm done to the Estonian people by the Soviet regime, the Estonian state implemented nationalistic policies that affected Russians and other non-Estonians. Thus, the members of the Russian minority needed to redefine their position within Estonia at a time when their presence and their links to Russia were perceived to be problematic by both the Estonian people and the state. When Estonia became a candidate to enter the European Union, the Estonian state was pressured to improve its relations with its national minorities, which led to the adoption of the Integration of non-Estonians policy. Conducted after implementation of the policy, this research examines the multifaceted aspect of the ethnic identity of Russian painters and authors living in Estonia. This thesis shows that they demonstrate a strong sense of belonging to Estonia, yet they manifest a deep attachment to the Russian language and culture, while also feeling related to Europe. This calls into question certain policies of the Estonian state, in particular those concerning the conditions of citizenship.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".